<h1 id="iowa-congressional-districts">2010 Iowa Congressional
Districts</h1>
<h2 id="redistricting-requirements">Redistricting requirements</h2>
<p>In Iowa, districts must:</p>
<ol type="1">
<li>be contiguous</li>
<li>have equal populations</li>
<li>be constructed only from counties</li>
<li>be geographically compact, as defined by two compactness measures:
<ol type="1">
<li>length-width compactness, which measures the total absolute
difference between the length and width of a district, across all
districts</li>
<li>perimeter compactness, which measures the total perimeter of all
districts</li>
</ol></li>
</ol>
<h3 id="algorithmic-constraints">Algorithmic Constraints</h3>
<p>We enforce a maximum population deviation of 0.01%, given strict
historical deviation standards. We also merge VTDs into counties and run
the simulation at the county level. For compactness, we increase the
<code>compactness</code> parameter to 1.1, which does not create too
much inefficiency.</p>
<h2 id="data-sources">Data Sources</h2>
<p>Data for Iowa comes from <a
href="https://redistricting.lls.edu/wp-content/uploads/ia_2010_congress_2011-04-19_2021-12-31.zip">All
About Redistricting</a></p>
<h2 id="pre-processing-notes">Pre-processing Notes</h2>
<p>No manual pre-processing decisions were necessary.</p>
<h2 id="simulation-notes">Simulation Notes</h2>
<p>We sample 8,000 districting plans for Iowa across four independent
runs of the SMC algorithm and randomly select 1,250 of the plans from
each of the four runs. As noted above, we set
<code>compactness=1.1</code>.</p>
<h2 id="contents">Contents</h2>
<ul>
<li><code>IA_cd_2010_stats.csv</code> contains summary statistics on the
sampled redistricting plans</li>
<li><code>IA_cd_2010_plans.rds</code> is a compressed
<code>redist_plans</code> object, which contains the matrix of
precinct/block assignments and may be used for further analysis.</li>
<li><code>IA_cd_2010_map.rds</code> is a compressed
<code>redist_map</code> object, which contains the precinct/block
shapefile and demographic data.</li>
</ul>
<p>Both the <code>redist_plans</code> and <code>redist_map</code> object
are intended to be used with the <a
href="https://alarm-redist.github.io/redist/">redist package</a>.</p>
<h3 id="codebook-for-summary-statistics">Codebook for summary
statistics</h3>
<ul>
<li><code>draw</code>: unique identifier for each sample. Non-numeric
draw names are real-world plans, e.g., <code>cd_2010</code> for an
enacted 2010 plan.</li>
<li><code>district</code>: a district identifier. District numbers
roughly match those in the enacted plan, but the correspondence is not
perfect.</li>
<li><code>chain</code>: a number identifying the run of the
redistricting algorithm used to produce this draw. Used for diagnostic
purposes.</li>
<li><code>pop_overlap</code>: a number indicating the fraction of people
in this plan who reside in the same-numbered district in the enacted
plan.</li>
<li><code>total_pop</code>: the total population of each district.</li>
<li><code>total_vap</code>: the total voting-aged population of each
district.</li>
<li><code>pop_*</code>, <code>vap_*</code>: total (voting-aged)
population within racial and ethnic groups for each district. Variable
codes documented <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>plan_dev</code>: the maximum population deviation among
districts in the plan. Computed as
<code>max(abs(distr_pop - target_pop)/target_pop)</code>.</li>
<li><code>comp_edge</code>: compactness, as measured by the fraction of
internal edges kept. Higher values indicate more compactness.</li>
<li><code>comp_polsby</code>: compactness, as measured by the
Polsby-Popper score. Higher values indicate more compactness.</li>
<li><code>county_splits</code>: the number of counties which belong to
more than one district.</li>
<li><code>muni_splits</code>: the number of Census Designated Places
which belong to more than one district.</li>
<li><code>*_##_dem_*</code>, <code>*_##_rep_*</code>: vote counts for
statewide Democratic and Republican candidates in a certain election.
More information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>adv_##</code>, <code>arv_##</code>: average vote counts for
statewide Democratic and Republican candidates in a certain year. More
information <a
href="https://github.com/alarm-redist/census-2020#data-format">here</a>.</li>
<li><code>ndv</code>, <code>nrv</code>: averages of the
<code>adv_##</code> and <code>arv_##</code> variables across all
available elections.</li>
<li><code>ndshare</code>: normal Democratic share, computed as
<code>ndv / (ndv + nrv)</code></li>
<li><code>e_dvs</code>: average Democratic vote share, computed as the
average of the Democratic vote share when first scored under each
statewide election.</li>
<li><code>pr_dem</code>: probability seat is represented by a Democrat;
calculated as the fraction of statewide elections under which the
district had a majority Democratic share.</li>
<li><code>e_dem</code>: expected number of Democratic seats for the
plan; equivalent to summing the <code>pr_dem</code> values across
districts</li>
<li><code>pbias</code>: partisan bias at 50% vote share, averaged across
all available elections. Positive values indicate Republican bias.</li>
<li><code>egap</code>: the efficiency gap, averaged across all available
elections. Positive values indicate Republican bias.</li>
</ul>
